AI Chatbot Engagement in Retail Banking (MSc Dissertation)
This project analysed customer interaction and feedback data to evaluate performance and user trust in AI chatbots. Natural language processing and sentiment analysis (BERT) techniques were used to identify engagement and quality drivers. The project provided actionable recommendations to improve chatbot outcomes and system effectiveness.• Applied NLP and sentiment analysis to chatbot interaction logs. • Evaluated driver factors for response quality and user engagement. • Delivered structured feedback to inform system refinements. • Contributed commercially relevant analysis for business outcomes.